Preserving the privacy of the personal
information, valuable company data, important records of
organizations become the difficult task day by day. Using
data mining technique in many applications, there are
various problems regarding security, privacy issue comes
front. There are lots of techniques used to maintain privacy
of data records. Transformation of data values is one of the
well known methods to maintain the privacy of data
records. This article presents LU-factorization method to
maintain the privacy of data records. Clustering techniques
had performed on the original and the distorted data sets.
Performance measures have been used to evaluate the
distorted data records with original data records. The
experimental result shows that the LU factorization
method maintains the balance between privacy and
accuracy. The accuracy of the clustering has been
measured and it produced acceptable results.
N. Maheswari : School of Computing Science and Engineering
VIT University, Chennai
Ankita Adhawale : School of Computing Science and Engineering
VIT University, Chennai
Amol Bhausaheb Wale : School of Computing Science and Engineering
VIT University, Chennai
Privacy Preserving, Data Distortion, Data
Mining, Clustering
This article proposes a new technique for privacy
preservation using LU-Factorization method. The
original datasets are transformed and the privacy
measures are applied to know the percentage of privacy
preservation. By applying the privacy measure to the existing system like SVD and PCA and comparing the
results with proposed method, it has been concluded that
LU-Factorization is better in preserving the privacy of
the dataset. Privacy measures and the misclassification
error results show the balance between clustering
accuracy and privacy.
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